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        <a href="/walker_sue/2021/05/20/week12-lr-woe/">逻辑回归与评分卡模型评价标准</a>
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          机器学习-BI


Week_12
逻辑回归与评分卡模型评价标准


逻辑回归与评分卡模型评价标准1.逻辑回归
逻辑回归假设数据服从伯努利分布，通过极大似然函数的方法，运用梯度下降来求解参数，来达到将数据二分类的目的。


2.评分卡评价标准2.1 评分卡模型的制作步骤 

数据预处理
变量衍生构造
变量分箱
变量挑选
模型参数估计
模型校验
概率转换为分数


2.2 模型的评价标准 
模型的区
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          机器学习-BI


Week_11
评分卡模型


评分卡模型一、评分卡模型评分卡模型： 

评分卡模型是常用的金融风控手段之一
风控，就是风险控制，我们采取各种措施和方法，减少风险发生的可能性，或风险发生时造成的损失


根据客户的各种属性和行为数据，利用信用评分模型，对客户的信用进行评分，从而决定是否给予授信，授信的额度和利率，减少在金融交易中存在的交易风险
按照不同的业务阶段，可以划分为三种
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        <a href="/walker_sue/2021/04/25/week10-rfm/">智能供应链与评分卡模型</a>
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        <a href="/walker_sue/2021/04/25/week10-rfm/">
          
          
            
          
          机器学习-BI


Week_10
智能供应链与评分卡模型


RFM模型1.概述什么是RFM RFM 模型是利用 R, F, M 三个特征去对用户进行划分的。其中R是表示最后一次付费的日期距离现在的时间, 比如你在 12月20号给一个主播打赏过, 那么到现在的距离的天数是5 那么R就是5, R是用来刻画用户的忠诚度, 一般来说R越小, 代表用户上一次刚刚才付费的, 这种用户的忠诚度比较高。F是表
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              <a href="/walker_sue/tags/RFM%E7%94%A8%E6%88%B7%E5%88%86%E5%B1%82/">RFM用户分层</a>
            
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        <a href="/walker_sue/2021/04/16/week9-car/">
          
          
            
          
          机器学习-BI


Week_09
模型融合与供应链预测


模型融合与供应链预测一、回归算法
1.常见的回归算法Linear Regression线性回归线性回归也被称为最小二乘回归，通常是人们在学习预测模型时首选的技术之一。在这种技术中，因变量是连续的，自变量可以是连续的也可以是离散的，回归线的性质是线性的。
Polynomial Regression多项式回归在分析数据的时候，我们会遇到不同
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        <a href="/walker_sue/2021/03/17/week8-rfm/">数据分析思维</a>
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        <a href="/walker_sue/2021/03/17/week8-rfm/">
          
          
            
          
          机器学习-BI


Week_08
数据分析思维


数据分析思维
1.数据分析的三种核心思维
数据分析思维——结构化,可以归纳为：核心论点、结构拆解、MECE（论点相互独立，完全穷尽）、验证等几个相关的步骤。
数据分析思维——公式化，公式法可以上下互为计算、且左右呈关联，另外公式法最为核心的就是：一切结构皆可优化直到最小不可分割。
数据分析思维——业务化，从业务角度去理解需要解决的问题

2.优
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        <a href="/walker_sue/2021/03/11/week7-alphago/">AlphaGo Zero实战</a>
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          机器学习-BI


Week_07
AlphaGo Zero实战


AlphaGO 实战五子棋AI工程：

game.py:定义了游戏的棋盘、获取棋盘状态，下棋（更新棋盘状态），判断是否有人获胜，绘制棋盘，两个player对弈，自我对弈
mcts_pure.py:实现了随机走子策略的MCTS（蒙特卡洛树搜索）
mcts_alphaZero.py:实现AlphaGo Zero中的MCTS（蒙特卡洛
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        <a href="/walker_sue/2021/03/08/week6-RL/">强化学习与推荐系统</a>
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Week_06
强化学习与推荐系统


Reinforcement Learning1.强化学习概述Reinforcement Learning 基本概念：

个体，Agent，学习器的角色，也称为智能体
环境，Environment，Agent之外一切组成的、与之交互的事物
动作，Action，Agent的行为
状态，State，Agent从环境获取的信息
奖励，Reward
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        <a href="/walker_sue/2021/02/26/week5-DIEN/">淘宝定向广告演化和天池天猫复购预测</a>
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          机器学习-BI


Week_05
淘宝定向广告演化和天池天猫复购预测


一、淘宝定向广告演化推荐系统的主要挑战之一，是同时解决Memorization和Generalization。Memorization根据历史行为数据，推荐通常和用户已有行为的物品直接相关的物品。而Generalization会学习新的特征组合，提高推荐物品的多样性。 DeepFM 中 Wide &amp; Deep 分别
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              2021-02-26
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              <a href="/walker_sue/categories/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E4%B8%AA%E6%80%A7%E5%8C%96%E6%8E%A8%E8%8D%90/">个性化推荐</a>
            
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      <h1 class="index-header">
        
        <a href="/walker_sue/2021/02/14/BI-week4-airbnb/">AIRBNB 个性化推荐与信用卡欺诈预测</a>
      </h1>

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        <a href="/walker_sue/2021/02/14/BI-week4-airbnb/">
          
          
            
          
          机器学习-BI


Week_04
个性化推荐


1. Airbnb个性化搜索推荐：Real-time Personalization using Embeddings for Search Ranking at Airbnb概述
KDD’2018 Best Paper
Airbnb的一个工业级工作，算法设计和Airbnb自身的业务有比较强的耦合

背景任务： Airbnb是一个沟通旅客和房主的
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          机器学习-BI


Week_03
中文文本处理


中文文本处理1. 分词与词性
分词:

NLTK库，对英文文本预处理



jieba库，对中文文本预处理
停用词（Stop Words）：需要自动过滤掉某些字或词
语料（Corpus）：一组原始文本的集合，用于无监督地训练文本


词性:

词性标注:名词/动词/形容词/助词…



命名实体识别: 人名（Nh）、机构名（Ni）、地名（Ns）
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